llmfan46/GLM-4-32B-0414-uncensored-heretic-v2
TEXT GENERATIONConcurrency Cost:2Model Size:32BQuant:FP8Ctx Length:32kPublished:Mar 17, 2026License:mitArchitecture:Transformer Open Weights Cold

llmfan46/GLM-4-32B-0414-uncensored-heretic-v2 is an uncensored variant of the GLM-4-32B-0414 model, developed by llmfan46 using the Heretic v1.2.0 Arbitrary-Rank Ablation (ARA) method. This 32 billion parameter model significantly reduces refusals by 93% (7/100 vs 100/100 for the original) while maintaining core model quality with a low KL divergence of 0.0555. It excels in instruction following, engineering code, function calling, and search-based Q&A, offering enhanced utility for applications requiring less content restriction.

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Model Overview

This model, llmfan46/GLM-4-32B-0414-uncensored-heretic-v2, is a decensored version of the original zai-org/GLM-4-32B-0414 model, created by llmfan46 using the Heretic v1.2.0 Arbitrary-Rank Ablation (ARA) method. The primary goal of this variant is to drastically reduce content refusals while preserving the original model's quality.

Key Differentiators

  • Significantly Reduced Refusals: Achieves a 93% reduction in refusals (7/100) compared to the original model (100/100), making it highly uncensored.
  • Quality Preservation: Maintains the original model's capabilities with a low KL divergence of 0.0555, indicating minimal degradation in performance.
  • GLM-4-32B Base: Built upon the GLM-4-32B-0414 series, a 32 billion parameter model pre-trained on 15T high-quality data, including reasoning-type synthetic data.
  • Enhanced Capabilities: The base GLM-4 model excels in instruction following, engineering code, artifact generation, function calling, search-based Q&A, and report generation.
  • Function Calling Support: Demonstrates robust function calling capabilities, allowing integration with external tools in JSON format.

Ideal Use Cases

  • Applications requiring minimal content restrictions or uncensored responses.
  • Tasks involving complex code generation and engineering solutions.
  • Scenarios demanding advanced function calling and tool integration.
  • Search-based Q&A and detailed report generation.
  • Use cases where preserving original model quality while removing censorship is critical.